A probabilistic contrast model of causal induction. (original) (raw)
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A test of the joint model of causal attribution
European journal of social psychology, 1997
The joint model integrates Mill's methods of difference and agreement for making causal attributions, and introduces a novel type of context attributions which reflect the opposite categories of the standard attribution responses provided in previous covariation research (external versus the person, general versus the stimulus, and stable versus the occasion). The joint model predicts that attributions to standard causes require Mill's method of difference and that attributions to context causes require Mill's method of agreement. Two empirical studies demonstrated that the joint model fitted adequately with all of subject's standard and context attribution responses, in contrast to earlier theorizing and data involving only the method of difference (cf. or only the method of agreement (cf. which received less empirical support.
Causal attribution from covariation information: the evidential evaluation model
European Journal of Social Psychology, 2002
It is hypothesized that causal attributions are made by transforming covariation information into evidence according to notions of evidential value, and that causal judgement is a function of the proportion of instances that are evaluated as confirmatory for the causal hypothesis under test: this is called the evidential evaluation model. An experiment was designed to test the judgemental rule in this model by setting up problems presenting consensus, distinctiveness, and consistency information in which the proportion of confirmatory instances varied but the objective contingency did not. It was found that judgements tended to vary with the proportion of confirmatory instances. Several other current models of causal judgement or causal attribution fail to account for this result. Similar findings have been obtained in studies of causal judgement from contingency information, so the present findings support an argument that the evidential evaluation model provides a unified account of judgement in both domains.
Developmental Psychology, 1980
Much current work in attribution theory presumes that in multicausal situations, naive attributions are often characterized by the multiple sufficient causal scheme. The present research was designed to examine whether the multiple sufficient scheme or an alternate model, the variant-effect scheme, better characterizes naive attributions. The variant-effect scheme is a generalization of Kelley's graded-effects scheme and, in contrast to the multiple sufficient scheme, reflects a belief in the conservation of causal energy. Five-to 12-yearolds received a series of social inference problems. In each problem, subjects gave base-rate estimates of an event and also made attributions of the likelihood that the event occurred after hearing that a related effect occurred in the presence of another cause. Three critical tests consistently disconfirmed use of the multiple sufficient scheme and supported use of the variant-effect scheme. The results further indicated increasing use of the variant-effect scheme with development. Preference for a variant-effect scheme over a multiple sufficient scheme suggests a picture of a naive attributor who is perceptually sophisticated but operationally naive-accepting causal simplicity rather than entertaining the possibility of causal indeterminacy.
From covariation to causation: A causal power theory.
Because causal relations are neither observable nor deducible, they must be induced from observable events. The 2 dominant approaches to the psychology of causal induction-the covariation approach and the causal power approach-are each crippled by fundamental problems. This article proposes an integration of these approaches thai overcomes these problems. The proposal is that reasoners innately treat the relation between covariation (a function denned in terms of observable events) and causal power (an unobservable entity) as that between scientists' law or model and their theory explaining the model. This solution is formalized in the power PC theory, a causal power theory of the probabilistic contrast model (P. W. Cheng & L. R. . The article reviews diverse old and new empirical tests discriminating this theory from previous models, none of which is justified by a theory. The results uniquely support the power PC theory.
… Journal of Experimental Psychology: Section B, 1998
Two experiments on human causal induction with multiple candidate causes are reported. Experiment 1 investigated the in¯uence of a perfect preventive cause on the ratings of a less contingent cause. Whereas the Rescorla± Wagner model (RWM) and Cheng' s probabilistic contrast model predict that the less contingent cause should be completely discounted, the Pearce model predicts, in most cases, an enhancement of that cause' s perceived importance. Results corresponded more closely to the predictions of the Pearce model. T he predictions of both the RWM and the Pearce model rely on a constant context cue acquiring associative strength, yet no such cue was explicitly identi® ed in the task scenario employed in Experiment 1. Experiment 2 replicated a number of key conditions of Experiment 1 with a task scenario that afforded ratings of the causal importance of the context in which the effectiveness of the discrete candidate causes was evaluated. In addition, the number of trials was increased to test the possibility that the ratings in Experiment 1 were the product of incomplete learning. T he results of the ® rst experiment were replicated and the ratings of the effectiveness of the context cue were anticipated by both the RWM and the Pearce model. Overall, the Pearce model offers a more comprehensive account of the causal inferences recorded in this study. In a causal induction task a number of candidate causes may precede the occurrence or absence of a target outcome. T he nature of the inductive inferences supported by one such candidate cause is in part determined by its predictive value as de® ned by the difference between the probability of the outcome given its presence, P(O | C), and given its absence, P(O | 2
Attribution of causality and the overjustification effect
1977
Page 1. 280 Attribution of Causality and the Overjustification Effect Thane S. Pittman, Eugenia E. Cooper, and Timothy W. Smithl Smoke Psychological Laboratories, Gettysburg College Abstract . Using false physiological feedback ...
Bayesian models of judgments of causal strength: A comparison.
We formulate four alternative Bayesian models of causal strength judgments, and compare their predictions to two sets of human data. The models were derived by factorially varying the causal generating function for integrating multiple causes (based on either the power PC theory or the ΔP rule) and priors on strengths (favoring necessary and sufficient (NS) causes, or uniform). The models based on the causal generating function derived from the power PC theory provided much better fits than those based on the function derived from the ΔP rule. The models that included NS priors were able to account for subtle asymmetries between strength judgments for generative and preventive causes. These results complement previous model comparisons for judgments of causal structure .
Self-Serving Biases In the Attribution of Causality: Fact or Fiction?
Psychological bulletin, 1975
A review of the evidence for and against the proposition that self-serving biases affect attributions of causality indicated that there is little empirical support for the proposition in its most general form. The literature provides some support for the contention that individuals engage in self-enhancing attributions under conditions of success, but only minimal evidence was found to suggest that individuals engage in self-protective attributions under conditions of failure. Moreover, it was proposed that the self-enhancing effect may not be due to motivational distortion, but rather to the tendency of people (a) to expect their behavior to produce success, (b) to discern a closer covariation between behavior and outcomes in the case of increasing success than in the case of constant failure, and (c) to misconstrue the meaning of contingency. We are prone to alter our perception of causality so as to protect or enhance our self esteem. We attribute success to our own dispositions and failure to external forces. (Hastorf, Schneider, & Polefka, 1970, p. 73) The principle described in the foregoing observation has received considerable attention in social psychology. Variously labeled ego-defensive, ego-protective, or ego-biased attribution, discussions of the phenomenon can be found in source books (